Advanced patient age is associated with inferior cancer‐specific survival after radical nephroureterectomy
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of patient age on outcomes after radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC). PATIENTS AND METHODS: Data were collected on 1453 patients treated with RNU at 13 centres. Pathological slides were reviewed by dedicated genitourinary pathologists according to standardized criteria. Age at RNU was analysed both as a continuous and categorical variable (<50, n = 85; 50-59.9, n = 229; 60-69.9, n = 416; 70-79.9, n = 523; > or =80 years, n = 200). RESULTS Patients aged <50 years were less likely to have undergone previous ureteroscopy and to have a history of bladder cancer (P < or = 0.026). Advanced age was associated with infiltrative architecture and female gender (P < or = 0.003). Patients aged >70 years were less likely to undergo lymphadenectomy and to receive adjuvant chemotherapy (P < or = 0.026). In multivariable analyses, being older was associated with decreased all-cause (AC) survival (>60 years) and cancer-specific survival (CSS; >80 years) after controlling for the effects of standard pathological features (P < or = 0.006). However, addition of age did not improve the predictive accuracy of a base model that included standard pathological features for prediction of either disease recurrence, AC survival or CSS. CONCLUSIONS: Being older at the time of RNU was associated with decreased survival. This finding could be due to a change in the biological potential of the tumour cell, a decrease in the host's defence mechanisms, or differences in care patterns. Further work is needed to improve our understanding of UTUC outcomes in this growing segment of the population and to develop strategies to improve cancer control in the elderly.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".